Information Thermodynamics for Deterministic Chemical Reaction Networks
Emanuele Penocchio, Francesco Avanzini, Massimiliano Esposito

TL;DR
This paper extends information thermodynamics to deterministic chemical reaction networks, introducing a mutual information concept for molecular features and deriving second laws for coupled subnetworks, with applications to self-assembly and molecular motors.
Contribution
It develops a framework for applying information thermodynamics to deterministic chemical networks, linking energy and information flows in coupled subnetworks.
Findings
Both systems involve two coupled chemical subnetworks.
External reservoirs drive one subnetwork out of equilibrium.
Information flow acts as an information ratchet only without energy flow.
Abstract
Information thermodynamics relates the rate of change of mutual information between two interacting subsystems to their thermodynamics when the joined system is described by a bipartite stochastic dynamics satisfying local detailed balance. Here, we expand the scope of information thermodynamics to deterministic bipartite chemical reaction networks, namely, composed of two coupled subnetworks sharing species, but not reactions. We do so by introducing a meaningful notion of mutual information between different molecular features, that we express in terms of deterministic concentrations. This allows us to formulate separate second laws for each subnetwork, which account for their energy and information exchanges, in complete analogy with stochastic systems. We then use our framework to investigate the working mechanisms of a model of chemically-driven self-assembly and an experimental…
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